AIMC Topic: Psychological Distress

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The Alongside Digital Wellness Program for Youth: Longitudinal Pre-Post Outcomes Study.

JMIR formative research
BACKGROUND: Youth are increasingly experiencing psychological distress. Schools are ideal settings for disseminating mental health support, but they are often insufficiently resourced to do so. Digital mental health tools represent a unique avenue to...

Assessing the accuracy and consistency of large language models in triaging social media posts for psychological distress.

Psychiatry research
Advances in artificial intelligence, particularly in natural language processing, offer promising tools for addressing mental health challenges in online contexts, potentially identifying at-risk individuals and informing timely interventions. This s...

Validating Emotion Analysis on Social Media Text for Detecting Psychological Distress: A Cross-Sectional Survey.

Issues in mental health nursing
This study investigates the relationship between self-reported psychological distress and emotions in social media posts, using a deep learning-based emotion analysis model. A cross-sectional design was used, collecting data from Instagram and Thread...

Face readers.

Science (New York, N.Y.)
Artificial intelligence is becoming better than humans at scanning animals' faces for signs of stress and pain. Are more complex emotions next?

Development and validation of a web-based calculator for determining the risk of psychological distress based on machine learning algorithms: A cross-sectional study of 342 lung cancer patients.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PURPOSE: Early and accurate identification of the risk of psychological distress allows for timely intervention and improved prognosis. Current methods for predicting psychological distress among lung cancer patients using readily available data are ...

An artificial intelligence tool to assess the risk of severe mental distress among college students in terms of demographics, eating habits, lifestyles, and sport habits: an externally validated study using machine learning.

BMC psychiatry
BACKGROUND: Precisely estimating the probability of mental health challenges among college students is pivotal for facilitating timely intervention and preventative measures. However, to date, no specific artificial intelligence (AI) models have been...

Decoding IBS: a machine learning approach to psychological distress and gut-brain interaction.

BMC gastroenterology
PURPOSE: Irritable bowel syndrome (IBS) is a diagnosis defined by gastrointestinal (GI) symptoms like abdominal pain and changes associated with defecation. The condition is classified as a disorder of the gut-brain interaction (DGBI), and patients w...

Factors influencing psychological distress among breast cancer survivors using machine learning techniques.

Scientific reports
Breast cancer is the most commonly diagnosed cancer among women worldwide. Breast cancer patients experience significant distress relating to their diagnosis and treatment. Managing this distress is critical for improving the lifespan and quality of ...

Virtual resonance: analyzing IPA usage intensity under COVID-19's isolating canopy.

Scientific reports
The widespread adoption of smartphones coupled with advancements in artificial intelligence has significantly propelled the use of intelligent personal assistants (IPAs). These digital assistants have become indispensable for many users, particularly...

Study of a PST-trained voice-enabled artificial intelligence counselor for adults with emotional distress (SPEAC-2): Design and methods.

Contemporary clinical trials
BACKGROUND: Novel and scalable psychotherapies are urgently needed to address the depression and anxiety epidemic. Leveraging artificial intelligence (AI), a voice-based virtual coach named Lumen was developed to deliver problem solving treatment (PS...